Tapani Raiko

1. Ladder Variational Autoencoders
   2016/02/06 by Casper Kaae Sønderby, Tapani Raiko, Sønderby, Casper Kaae +7 · 39 citations
   Computer Science · #Generative Adversarial Networks and Image Synthesis #Topic Modeling #Machine Learning in Healthcare
2. Semi-Supervised Learning with Ladder Networks
   2015/07/09 by Antti Rasmus, Harri Valpola, Rasmus, Antti +7 · 32 citations
   Computer Science · #Anomaly Detection Techniques and Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE)
3. Iterative Neural Autoregressive Distribution Estimator (NADE-k)
   2014/06/05 by Tapani Raiko, Raiko, Tapani, Li Yao +5 · 7 citations
   Computer Science · #Generative Adversarial Networks and Image Synthesis #Gaussian Processes and Bayesian Inference #Domain Adaptation and Few-Shot Learning
4. DopeLearning
   2015/05/18 by Eric Malmi, Pyry Takala, Hannu Toivonen +2 · 1 voice
   Computer Science · #Topic Modeling #Music and Audio Processing #Artificial Intelligence in Games
5. Techniques for Learning Binary Stochastic Feedforward Neural Networks
   2014/06/11 by Tapani Raiko, Raiko, Tapani, Mathias Berglund +5 · 3 citations
   Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE)
6. Stochastic Gradient Estimate Variance in Contrastive Divergence and\n Persistent Contrastive Divergence
   2013/12/20 by Mathias Berglund, Tapani Raiko, Berglund, Mathias +1 · 1 citation
   Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #62M45 #Advanced Electron Microscopy Techniques and Applications #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural and Evolutionary Computing (cs.NE) #Stochastic Gradient Optimization Techniques